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June, 1994 Asymptotic Bayes Criteria for Nonparametric Response Surface Design
Toby Mitchell, Jerome Sacks, Donald Ylvisaker
Ann. Statist. 22(2): 634-651 (June, 1994). DOI: 10.1214/aos/1176325488

Abstract

This paper deals with Bayesian design for response surface prediction when the prior may be finite or infinite dimensional, the design space arbitrary. In order that the resulting problems be manageable, we resort to asymptotic versions of D-, G- and A-optimality. Here the asymptotics stem from allowing the error variance to be large. The problems thus elicited have strong game-like characteristics. Examples of theoretical solutions are brought forward, especially when the priors are stationary processes on an interval, and we give numerical evidence that the asymptotics work well in the finite domain.

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Toby Mitchell. Jerome Sacks. Donald Ylvisaker. "Asymptotic Bayes Criteria for Nonparametric Response Surface Design." Ann. Statist. 22 (2) 634 - 651, June, 1994. https://doi.org/10.1214/aos/1176325488

Information

Published: June, 1994
First available in Project Euclid: 11 April 2007

zbMATH: 0815.62050
MathSciNet: MR1292533
Digital Object Identifier: 10.1214/aos/1176325488

Subjects:
Primary: 62K05
Secondary: 62J02

Rights: Copyright © 1994 Institute of Mathematical Statistics

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Vol.22 • No. 2 • June, 1994
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